Automating business processes with AI: where to actually start

Most AI projects fail because of the wrong first use case.

70% of corporate AI projects never reach production — wrong first-process selection.

Volume × Repetition × Error tolerance

Good candidates: high volume, high repetition, non-zero error tolerance.

Works: customer triage, invoice extraction, contract drafts, internal manual search.

Fails: critical medical decisions, payroll, strategic one-offs.

1. Customer service triage. 2. Internal RAG KB. 3. Document extraction. 4. Lead scoring. 5. Operational content generation.

No-code covers 70%. Custom only for proprietary integrations, scale, specific compliance.

Automating processes humans don't understand. Skipping shadow mode. Picking models by hype. Underestimating observability.

Time per request, cost per execution, human intervention rate, satisfaction, monthly ROI.